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Estimation of Messaging Overhead Distributed Detection and Inference (DDI)

Estimation of Messaging Overhead Distributed Detection and Inference (DDI). Soumya Sen (UPenn), Supervisors: Carl Livadas, Eve Schooler, DDI team. Objective – Understand overhead of DDI messaging Challenge – Design/evaluate scalable scheme for membership maintenance

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Estimation of Messaging Overhead Distributed Detection and Inference (DDI)

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  1. Estimation of Messaging Overhead Distributed Detection and Inference (DDI) Soumya Sen (UPenn), Supervisors: Carl Livadas, Eve Schooler, DDI team • Objective – Understand overhead of DDI messaging • Challenge – Design/evaluate scalable scheme for membership maintenance • Approach – Implement a gossip-based messaging and membership scheme • Achievement –Evaluation of effect of packet duplication on detection The DDI System Architecture Messaging & Membership Scheme • Local Detectors (LDs) gossip their Local Reports (LRs) to random subset of Global Detectors (GDs) • LDs and GDs maintain random partial membership view • Membership views exchanged between LDs and GDs to ensure view uniformity and prevent node isolation and overlay partition • Challenges: Bootstrapping, Isolation Recovery, Partition Prevention/Recovery, Un-subscriptions Effect of LR Duplication on Detection Extent of LR duplication Fig: % of non-duplicate LRs Vs Effective Fanout Fig. Effect of varying effective fanout on worm detection

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